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The (standard) Boolean model of information retrieval (BIR) [1] is a classical information retrieval (IR) model and, at the same time, the first and most-adopted one. [2] The BIR is based on Boolean logic and classical set theory in that both the documents to be searched and the user's query are conceived as sets of terms (a bag-of-words model ).
The Extended Boolean model was described in a Communications of the ACM article appearing in 1983, by Gerard Salton, Edward A. Fox, and Harry Wu. The goal of the Extended Boolean model is to overcome the drawbacks of the Boolean model that has been used in information retrieval. The Boolean model doesn't consider term weights in queries, and ...
Most search engines support the use of the Boolean operators AND, OR and NOT to help end users refine the search query. Boolean operators are for literal searches that allow the user to refine and extend the terms of the search. The engine looks for the words or phrases exactly as entered.
A concept search (or conceptual search) is an automated information retrieval method that is used to search electronically stored unstructured text (for example, digital archives, email, scientific literature, etc.) for information that is conceptually similar to the information provided in a search query.
This example of the Pareto principle (or 80–20 rule) allows search engines to employ optimization techniques such as index or database partitioning, caching and pre-fetching. In addition, studies have been conducted into linguistically-oriented attributes that can recognize if a web query is navigational, informational or transactional.
In industrial search engines, such as LinkedIn, federated search is used to personalize vertical preference for ambiguous queries. [2] For instance, when a user issues a query like "machine learning" on LinkedIn, he or she could mean to search for people with machine learning skill, jobs requiring machine learning skill or content about the topic.
1. Go to AOL Mail. 2. Next to the search box, click the Drop down icon . 3. Select the part of your account you want to search. 4. Click the Search icon.
Ranking of query is one of the fundamental problems in information retrieval (IR), [1] the scientific/engineering discipline behind search engines. [2] Given a query q and a collection D of documents that match the query, the problem is to rank, that is, sort, the documents in D according to some criterion so that the "best" results appear early in the result list displayed to the user.